Jove
Visualize
Contact Us
JoVE
x logofacebook logolinkedin logoyoutube logo
ABOUT JoVE
OverviewLeadershipBlogJoVE Help Center
AUTHORS
Publishing ProcessEditorial BoardScope & PoliciesPeer ReviewFAQSubmit
LIBRARIANS
TestimonialsSubscriptionsAccessResourcesLibrary Advisory BoardFAQ
RESEARCH
JoVE JournalMethods CollectionsJoVE Encyclopedia of ExperimentsArchive
EDUCATION
JoVE CoreJoVE BusinessJoVE Science EducationJoVE Lab ManualFaculty Resource CenterFaculty Site
Terms & Conditions of Use
Privacy Policy
Policies

Filters

Ozgur Kisi

Showing results (1-10 of 45) with videos related to

Pageof 5
Sort By:
Environmental Science and Pollution Research International|June 1, 2017
Extreme learning machines: a new approach for modeling dissolved oxygen (DO) concentration with and without water quality variables as predictorsSalim Heddam, Ozgur Kisi
Environmental Science and Pollution Research International|May 3, 2020
Transfer learning for neural network model in chlorophyll-a dynamics prediction by Wenchong Tian, Zhenliang Liao, and Xuan WangRana Muhammad Adnan, Ozgur Kisi
Environmental Science and Pollution Research International|January 12, 2020
Dissolved oxygen prediction using a new ensemble methodOzgur Kisi, Meysam Alizamir, AliReza Docheshmeh Gorgij
The Science of the Total Environment|June 9, 2020
Comments on "Predicting permeability changes with injecting CO2 in coal seams during CO2 geological sequestration: A comparative study among six SVM-based hybrid models" Science of the Total Environment, 705, 135941 (2020)Rana Muhammad Adnan, Zhongmin Liang, Ozgur Kisi
Peerj|September 1, 2020
Spatial modeling of long-term air temperatures for sustainability: evolutionary fuzzy approach and neuro-fuzzy methodsAbolghasem Sadeghi-Niaraki, Ozgur Kisi, Soo-Mi Choi
Environmental Science and Pollution Research International|September 10, 2024
Hybrid machine learning approach integrating GMDH and SVR for heavy metal concentration prediction in dust samplesJamshid Piri, Mohammad Reza Rezaei Kahkha, Ozgur Kisi
Environmental Science and Pollution Research International|June 8, 2019
Evaluating the performance of four different heuristic approaches with Gamma test for daily suspended sediment concentration modelingAnurag Malik, Anil Kumar, Ozgur Kisi, et al.
Foodborne Pathogens and Disease|June 14, 2012
Application of non-linear models to predict inhibition effects of various plant hydrosols on Listeria monocytogenes inoculated on fresh-cut applesIsmet Ozturk, Fatih Tornuk, Osman Sagdic, et al.
Scientific Reports|November 12, 2025
Deep learning approach to energy consumption modeling in wastewater pumping systemsJamshid Piri, Babak Masoudi, Mohammad Salkhordeh Haghighi, et al.
Environmental Science and Pollution Research International|May 24, 2020
Artificial intelligence models versus empirical equations for modeling monthly reference evapotranspirationYazid Tikhamarine, Anurag Malik, Doudja Souag-Gamane, et al.
Pageof 5

Showing results (1-10 of 45) with videos related to

Sort By:
Pageof 5
Environmental Science and Pollution Research International|June 1, 2017
Extreme learning machines: a new approach for modeling dissolved oxygen (DO) concentration with and without water quality variables as predictorsSalim Heddam, Ozgur Kisi
Environmental Science and Pollution Research International|May 3, 2020
Transfer learning for neural network model in chlorophyll-a dynamics prediction by Wenchong Tian, Zhenliang Liao, and Xuan WangRana Muhammad Adnan, Ozgur Kisi
Environmental Science and Pollution Research International|January 12, 2020
Dissolved oxygen prediction using a new ensemble methodOzgur Kisi, Meysam Alizamir, AliReza Docheshmeh Gorgij
The Science of the Total Environment|June 9, 2020
Comments on "Predicting permeability changes with injecting CO2 in coal seams during CO2 geological sequestration: A comparative study among six SVM-based hybrid models" Science of the Total Environment, 705, 135941 (2020)Rana Muhammad Adnan, Zhongmin Liang, Ozgur Kisi
Peerj|September 1, 2020
Spatial modeling of long-term air temperatures for sustainability: evolutionary fuzzy approach and neuro-fuzzy methodsAbolghasem Sadeghi-Niaraki, Ozgur Kisi, Soo-Mi Choi
Environmental Science and Pollution Research International|September 10, 2024
Hybrid machine learning approach integrating GMDH and SVR for heavy metal concentration prediction in dust samplesJamshid Piri, Mohammad Reza Rezaei Kahkha, Ozgur Kisi
Environmental Science and Pollution Research International|June 8, 2019
Evaluating the performance of four different heuristic approaches with Gamma test for daily suspended sediment concentration modelingAnurag Malik, Anil Kumar, Ozgur Kisi, et al.
Foodborne Pathogens and Disease|June 14, 2012
Application of non-linear models to predict inhibition effects of various plant hydrosols on Listeria monocytogenes inoculated on fresh-cut applesIsmet Ozturk, Fatih Tornuk, Osman Sagdic, et al.
Scientific Reports|November 12, 2025
Deep learning approach to energy consumption modeling in wastewater pumping systemsJamshid Piri, Babak Masoudi, Mohammad Salkhordeh Haghighi, et al.
Environmental Science and Pollution Research International|May 24, 2020
Artificial intelligence models versus empirical equations for modeling monthly reference evapotranspirationYazid Tikhamarine, Anurag Malik, Doudja Souag-Gamane, et al.
Pageof 5